Single-molecule techniques based on fluorescence detection are exceedingly useful in revealing chemical and/or physical properties of individual molecules that are otherwise unobtainable via traditional ensemble measurements. However, in solution Brownian motions prevent the observation of individual molecules for an extended period of time. While many confinement strategies have been developed to overcome this limitation, they suffer various drawbacks (e.g., photobleaching under constant light illumination). Thus, we aim to develop new experimental approaches, based on the use of microfabricated nano- and/or micro-chambers, to confine individual molecules, to significantly reduce the rate of photobleaching, and to enhance the sensitivity of single-molecule detection.

The proposed research addresses the fundamental chemical-physics and engineering of micro and nanoscopic power storage devices. A device now called supercabatteries that combines charge storage by Faradaic redox processes in Electro-Active Polymers (EAP) comprising the battery part, and Double Layer Capacitance (DLC) the super-capacitor part. These are subsystems purposely designed to energize micro and nanoscopic electrical / electronic devices, this time including those designed to be ted in humans.

TUNING THE MECHANICAL PROPERTIES OF FIBRIN GELS BY ALTERING THE NANOSCALE STRUCTURE OF FIBRIN

Prashant Purohit
Mechanical Engineering and Applied Mechanics (MEAM)

The long term goal of this project is to use the most highly variable and modifiable part of fibrin at the nano scale, the alphaC region, to create new materials with precisely tunable mechanical and structural properties such as high Poisson's ratio, high porosity and biodegradability. This research is based on our finding that unfolding of fibrin monomers at the nanoscale is behind the unusual mechanical properties of fibrin at the macroscale. The aims of this innovation award project are to study experimentally the role of the alphaC region in fibrin's mechanical properties and to develop a predictive quantitative model to account for these properties.